For robots to gain skills such as manipulation, learning-based methods have received more attention recently due to their capability in handling the complexity in robot perception. For instance, a number of 6D object pose estimation methods using deep neural networks are introduced for model-based grasping [1]}, [2]}. Learning techniques also demonstrate impressive performance in grasping unknown objects [3]}, [4]}, [5]}. It is well known that training deep neural networks requires a significant amount of data. How to obtain training data becomes the bottleneck in applying learning techniques to different robotic problems these days.
